Hi, I'm trying to fit a logit model to a set of data that was collected under a split plot scheme. The structure of the data is
Whole plot factors: Watering Frequency (2 levels: Hi/Lo) and Fertilizer type (3 factors A/B/C) Subplot factor: slope type (2 factors up/down) Response: Proportion of infected leaves(Infected leaves/Total leaves) of the plant (2 plants recorded from each plot) Dataset (Partial) Water Fert Slope Plant Total Infect Hi A up 1 24 2 Hi A up 2 31 1 Hi A down 1 21 0 Hi A down 2 34 0 Hi ... Hi ... Lo Lo All of the factors (Whole plot and subplot) are fixed In addition there are a lot of plants that are not affected at all, so there are lot zeros I'm trying to use the vglm function in VGAM package with zibinomial distribution. I'm a little confused about how to input the covariates to indicate a split plot design. My first try was bmod<-vglm(cbind(Infect, Total)~Water*Fert+Slope/(Water*Fert), zibinomial, data=FertPlots) I would like to know if the syntax I have used in the predictors is right for the split plot model. If not, how do I give the split plot model in R. summary(bmod) does not give any p-values for individual tests or a degrees of freedom to test them. How do I test these factors using the vglm function? Thank you Dilan Paranagama ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
